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A Resource Comparison of Logical T-State Preparation

arXiv Quantum Physics
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Researchers compared three key methods for preparing fault-tolerant logical T-states—magic state distillation, cultivation, and code switching—highlighting their trade-offs under varying noise models and cost metrics. Magic state distillation achieves the lowest output error rates but demands higher resource costs, making it ideal for ultra-low-error applications like cryptographic algorithms. Code switching offers the lowest single-attempt cost and smallest physical qubit footprint, positioning it as the most space-efficient option for near-term fault-tolerant systems. Recent RP2 cultivation protocols bridge the gap with moderate costs and error rates between 1e-6 and 1e-9, providing a balanced alternative for intermediate-scale quantum computing. A case study using Shor’s algorithm error budgets demonstrates how these preparation routes impact full-workload efficiency, clarifying real-world deployment trade-offs.
A Resource Comparison of Logical T-State Preparation

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Quantum Physics arXiv:2605.26522 (quant-ph) [Submitted on 26 May 2026] Title:A Resource Comparison of Logical T-State Preparation Authors:Jianshuo Gao, Xiao Yuan, Yuan Yao View a PDF of the paper titled A Resource Comparison of Logical T-State Preparation, by Jianshuo Gao and 1 other authors View PDF HTML (experimental) Abstract:Logical T state preparation is a major overhead source in fault tolerant architectures built from stabilizer operations. Existing protocols, however, are reported under different code families, noise models, postselection rules, and cost conventions, making direct comparison difficult. We compare three representative preparation routes: magic state distillation, magic state cultivation, and code switching, using currently available results. Rather than reducing heterogeneous data to a single cost metric, we retain source native cost units and record output error, single attempt cost, expected cost per accepted output, footprint, latency, and reporting completeness for each configuration. Within the current dataset, distillation reaches the lowest output error regime; code switching achieves the lowest reported single attempt cost and the smallest explicit footprint among the compatible rows; and recent RP2 cultivation results add low cost cultivation points with output errors between 1e-6 and 1e-9. As a simple algorithm level case study, we also examine the reported preparation routes under an error budget motivated by Shor factoring algorithm, in order to relate single state preparation costs to full workload requirements. The resulting comparison clarifies the trade offs currently supported across the literature, while remaining bounded by the conventions and coverage of the underlying papers. Subjects: Quantum Physics (quant-ph) Cite as: arXiv:2605.26522 [quant-ph] (or arXiv:2605.26522v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2605.26522 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Jianshuo Gao [view email] [v1] Tue, 26 May 2026 04:09:50 UTC (142 KB) Full-text links: Access Paper: View a PDF of the paper titled A Resource Comparison of Logical T-State Preparation, by Jianshuo Gao and 1 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-05 References & Citations INSPIRE HEP NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)

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Source: arXiv Quantum Physics